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                <p style="padding-top: 0pt; " class="paragraph_style">Research<br /></p>
                <p style="padding-bottom: 0pt; " class="Quote">Natural Language Processing (NLP)</p>
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                <p style="padding-top: 0pt; " class="paragraph_style_1">Abstractive Summarization<br /></p>
                <p class="paragraph_style_2">Most automatic summarization techniques rank the relative importance of sentences in the original document and extract the most important ones to build the summary. However, in order to produce a unified summary of both the text and graphics in a multi-modal document, we must integrate the knowledge obtained from both at the conceptual level. As we are unlikely to find sentences in the original article that capture the integrated information from both the text and graphics, we must create an abstractive summary by generating novel sentences to express the key concepts found in the source document. Our line of research is intended to accomplish this task.<br /></p>
                <p class="paragraph_style_2">Resources:  <a title="http://www.cis.udel.edu/~charlieg/corpora" href="http://www.cis.udel.edu/~charlieg/corpora">Corpora</a><br /></p>
                <p class="paragraph_style_2"><br /><span class="style">Assistive Technologies<br /></span></p>
                <p class="paragraph_style_2">Artificial Intelligence and Natural Language Processing can be used in many different ways to benefit people with disabilities. By providing an alternate means of communicating information, we can help increase universal access for everyone. As a member of the Human Language Technologies lab, I've contributed to several projects for people with hearing and visual impairments. My current work explores applications designed to improve web accessibility via the non-visual presentation of information.<br /></p>
                <p class="paragraph_style_2">Projects:  <a title="http://www.cis.udel.edu/~demir/SIGHT/main.html" href="http://www.cis.udel.edu/~demir/SIGHT/main.html">SIGHT</a>  <a title="http://www.eecis.udel.edu/research/icicle" href="http://www.eecis.udel.edu/research/icicle">ICICLE</a><br /></p>
                <p class="paragraph_style_2"><br /><span class="style">Referring Expression Generation<br /></span></p>
                <p class="paragraph_style_2">The production of referring expressions by natural language generation systems presents a considerable challenge, including simply determining which type of reference (name vs. pronoun, etc.) is most appropriate in a given context. Overuse of names sounds awkward and unnatural, while overuse of pronouns can introduce ambiguity and be difficult to follow. The focus of our work is to combine techniques from computational linguistics with insights from psycholinguistic research to develop systems which mimic human reference generation.<br /></p>
                <p style="padding-bottom: 0pt; " class="paragraph_style_2">Projects:  <a title="http://www.itri.brighton.ac.uk/research/genchal09/grec/" href="http://www.itri.brighton.ac.uk/research/genchal09/grec/">GREC 2009</a>  <a title="http://www.itri.brighton.ac.uk/research/genchal10/grec/" href="http://www.itri.brighton.ac.uk/research/genchal10/grec/">GREC 2010</a></p>
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